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running-smoke-tests

running-smoke-tests

Execute fast smoke tests validating critical functionality after deployment. Use when performing specialized testing. Trigger with phrases like "run smoke tests", "quick validation", or "test critical paths".

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill 문서

GitHub

name: running-smoke-tests description: 'Execute fast smoke tests validating critical functionality after deployment.

Use when performing specialized testing.

Trigger with phrases like "run smoke tests", "quick validation", or "test critical paths".

' allowed-tools: Read, Write, Edit, Grep, Glob, Bash(test:smoke-*) version: 1.20.0 author: Jeremy Longshore jeremy@intentsolutions.io license: MIT tags:

  • testing
  • deployment
  • smoke-tests compatibility: Designed for Claude Code

Smoke Test Runner

Overview

Execute fast, high-confidence smoke tests that validate critical application functionality after deployment or build. Smoke tests verify that the application starts, core user flows work, and key integrations respond -- without running the full test suite.

Prerequisites

  • Application deployed and accessible at a known URL or running locally
  • HTTP client available (curl, wget, node-fetch, or Playwright)
  • List of critical endpoints and user flows to validate
  • Expected response codes and content patterns for each check
  • CI/CD pipeline hook for post-deployment validation

Instructions

  1. Identify the critical paths that constitute a "working" application:
    • Health check endpoint returns 200 with expected body.
    • Homepage loads and contains key UI elements.
    • Authentication flow succeeds with test credentials.
    • Primary API endpoint returns valid data.
    • Database connection is active and responding.
  2. Create a smoke test configuration listing each check:
    • URL or command to execute.
    • Expected HTTP status code (200, 301, etc.).
    • Response body pattern to match (substring or regex).
    • Maximum acceptable response time (e.g., 3 seconds).
  3. Write the smoke test suite as a lightweight script or test file:
    • Use curl for HTTP checks or Playwright for browser-based checks.
    • Run checks sequentially for simplicity (parallel for speed if independent).
    • Fail fast on the first critical failure.
    • Log each check result with pass/fail, response time, and status code.
  4. Implement timeout guards:
    • Set a global timeout of 60 seconds for the entire smoke suite.
    • Set per-check timeouts of 5-10 seconds.
    • Treat timeouts as failures, not retries.
  5. Add deployment-gate integration:
    • On success: proceed with deployment promotion or traffic shifting.
    • On failure: trigger rollback and send alert notification.
    • Report results to CI/CD dashboard and Slack/Teams webhook.
  6. Store smoke test results as CI artifacts for audit trail.
  7. Schedule periodic smoke runs (every 5 minutes in production) as synthetic monitoring.

Output

  • Smoke test script (scripts/smoke-test.sh or tests/smoke.test.ts)
  • Pass/fail result for each critical check with response times
  • Deployment gate verdict (PASS or FAIL with reason)
  • CI artifact with timestamped smoke test log
  • Alert payload for failed checks (Slack webhook, PagerDuty, etc.)

Error Handling

ErrorCauseSolution
Connection refusedApplication not yet ready after deploymentAdd a startup wait with exponential backoff (max 30 seconds) before running smoke tests
503 Service UnavailableApplication is starting or behind a load balancer drainingRetry with 2-second delay up to 3 times; check load balancer health check status
Unexpected redirect (301/302)URL changed or SSL redirect not accounted forFollow redirects with curl -L; update expected URLs in smoke config
Content mismatchPage content changed but smoke test pattern is too specificUse broad patterns (check for <title> or key element IDs, not exact text)
Timeout on database checkDatabase migration running or connection pool exhaustedIncrease timeout for database checks; verify migration completed before smoke tests

Examples

Shell-based smoke test script:

#!/bin/bash
set -e
BASE_URL="${1:-http://localhost:3000}"  # 3000: 3 seconds in ms
PASS=0; FAIL=0

check() {
  local name="$1" url="$2" expected="$3"
  status=$(curl -s -o /dev/null -w '%{http_code}' --max-time 5 "$url")
  if [ "$status" = "$expected" ]; then
    echo "PASS: $name (HTTP $status)"
    ((PASS++))
  else
    echo "FAIL: $name (expected $expected, got $status)"
    ((FAIL++))
  fi
}

check "Health check" "$BASE_URL/health" "200"  # HTTP 200 OK
check "Homepage" "$BASE_URL/" "200"  # HTTP 200 OK
check "API status" "$BASE_URL/api/status" "200"  # HTTP 200 OK
check "Login page" "$BASE_URL/login" "200"  # HTTP 200 OK

echo "Results: $PASS passed, $FAIL failed"
[ "$FAIL" -eq 0 ] || exit 1

Playwright smoke test:

import { test, expect } from '@playwright/test';

test('homepage loads with navigation', async ({ page }) => {
  await page.goto('/', { timeout: 10000 });  # 10000: 10 seconds in ms
  await expect(page.locator('nav')).toBeVisible();
  await expect(page).toHaveTitle(/My App/);
});

test('API health endpoint responds', async ({ request }) => {
  const response = await request.get('/api/health');
  expect(response.ok()).toBeTruthy();
  expect(await response.json()).toHaveProperty('status', 'ok');
});

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